The Gastrointestinal Phenotype of Germline Biallelic Mismatch Repair Gene Mutations
Bibliographic record
Abstract
OBJECTIVES: A novel cancer syndrome associated with biallelic mismatch repair (MMR) mutations has been described recently. Patients presenting with childhood-onset gastrointestinal (GI) cancers may carry biallelic MMR mutations and have a distinct phenotype from classic Lynch syndrome. The aim of this study was to characterize patients with GI small bowel and/or colorectal cancers (CRCs) who have germline biallelic MMR mutations. METHODS: A search of a Canadian GI cancer registry and literature review to identify patients with biallelic MMR was conducted. RESULTS: The database identified 237 patients with intestinal cancer diagnosed before the age of 35 years. Five (2.1%) patients had biallelic MMR mutations. Overall, 32 individuals, from 29 families, with biallelic MMR gene mutations and GI cancers were identified by the registry and literature review. Among the 29 patients with CRCs, the mean age of first cancer diagnosis was 16.4 years (range: 5-28). More than one-third of patients had multiple colorectal adenomas (>10 polyps). Six individuals with biallelic MMR gene mutations have been reported with small bowel adenocarcinoma (mean age 20 years (range: 11-41)). Café-au-lait (CAL) macules were reported in 72% and, based on mutation analysis, consanguinity was suspected in 52% of kindred. Of the 29 kindred, 19 (66%) had PMS2 mutations, 6 (21%) had MSH6 mutations, 3 (10%) had MLH1 mutations, and 1 (3%) had MSH2 mutation. CONCLUSIONS: Biallelic MMR mutations are an underrecognized cause of small bowel and colonic cancers in children and young adults. This distinct phenotype includes multiple adenomatous polyps and CAL skin lesions. It is important to identify such patients, so that families can be referred for genetic testing and counseling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".